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Green is a clean, colorful test runner for Python unit tests. Compare it to nose or trial.

Latest Version: 2.12.1


Clean, colorful test runner for Python

Green is a clean, colorful test runner for Python unit tests. Compare it to
[nose]( or

Green grew out of a desire to see pretty colors. Really! A big part of the
whole the **Red/Green/Refactor** process in test-driven-development is
_actually getting to see red and green output_. Most python unit testing
actually goes **Gray/Gray/Refactor** (at least on my terminal, which is gray
text on black background). That's a shame. Even TV is in color these days.
Why not terminal output? Even worse, the default output for most test runners
is cluttered, hard-to-read, redundant, and the dang statuses are not aligned
vertically! Green fixes all that.

### Features ###

- **Colorful** - Terminal output makes good use of color when the terminal supports it.
- **Clean** - Vertically-aligned statuses. Low redundancy in output.
- **Fast** - Can run tests in independent subprocesses.
- **Powerful** - Multi-target + auto-discovery.
- **Traditional** - Use the normal `unittest` classes and methods for your unit tests.
- **Descriptive** - Four verbosity levels, from just dots to full docstring output.
- **Thorough** - Built-in, optional integration with
- **Modern** - Supports Python 2.7, 3.3, 3.4, and [PyPy](
- **Portable** - Completely supports OS X, Linux, and BSDs (and maybe Windows).
- **Flexible** - Optional HTML output.

Basic Usage

You may need to prepend the installation command with `sudo` or run it as root
if your normal user cannot write to the local Python package directory.

pip3 install green # To upgrade: "pip3 install --upgrade green"

To run existing unit tests, navigate to the *parent* directory of your project.

cd /parent/directory

Then pass green the directory of your project and let it autodiscover the tests
(assuming the test modules, classes, and methods all start with 'test').

green yourproject

If your tests are extremely simple (don't attempt absolute imports), or if you
carefully set up your `PYTHONPATH` environment variable to include the parent
path of your project, you may be able to just run `green` from _inside_ your
project directory.

export PYTHONPATH=/parent/directory
cd /parent/directory/yourproject

Verbosity Levels

By default, Green mimics the verbosity levels of vanilla unittest, meaning that
output is mostly just dots. For Green we recommend adding more verbosity by
using the `-v` or `-vv` options.

- `default` - Dots, tracebacks, and summary line.
- `-v` - Add module/class heirarchy and function names
- `-vv` - Version information added. Function names are replaced with first line of docstring.
- `-vvv` - Highest verbosity level recognized. Details coming soon.

See the section entitled [Running Green](#running-green) for example output.

Canned Examples

To see all examples of all the failures, errors, etc. that could occur:

green green.examples

To run Green's own internal unit tests:

green green

Advanced Usage

Please see `green --help`

Unit Test Structure Tutorial

This tutorial *does* cover:

- External structure of your project (directory and file layout)
- Skeleton of a real test module
- How to import stuff from from your project into your test module
- Gotchas about naming...everything.
- Where to run green from and what the output could look like.

This tutorial *does not* cover:

- [Why you should write unit tests at
- The benefits of [Test-Driven
- How to use the [unittest]( module.
- How to write
unit tests.

### External Structure ###

This is what your project layout should look like with just one module in your

proj # 'proj' is the package
├── # 'foo' (or is the only "real" module
└── test # 'test' is a sub-package
└── # 'test_foo' is the only "test" module


1. There is an `` in every directory. Don't forget it. It can be
an empty file, but it needs to exist.

2. `proj` itself is a directory that you will be storing somewhere. We'll
pretend it's in `/home/user`

3. The `test` directory needs to start with `test`.

4. The test modules need to start with `test`.

When your project starts adding code in sub-packages, you will need to make a
choice on where you put their tests. I prefer to create a `test` subdirectory
in each sub-package.

├── subpkg
│   ├──
│   ├──
│   └── test # test subdirectory in every sub-package
│   ├──
│   └──
└── test

The other option is to start mirroring your subpackage layout from within a single test directory.

├── subpkg
│   ├──
│   ├──
└── test
├── subpkg # mirror sub-package layout inside test dir
│   ├──
│   └──

### Skeleton of Test Module ###

Assume `` contains the following contents:

def answer():
return 42

class School():

def food(self):
return 'awful'

def age(self):
return 300

Here's a possible version of `` you could have.

# Import stuff you need for the unit tests themselves to work
import unittest

# Import stuff that you want to test. Don't import extra stuff if you don't
# have to.
from import answer, School

# If you need the whole module, you can do this:
# from proj import foo
# Here's another reasonable way to import the whole module:
# import as foo
# In either case, you would obviously need to access objects like this:
# foo.answer()
# foo.School()

# Then write your tests

class TestAnswer(unittest.TestCase):

def test_type(self):
"answer() returns an integer"
self.assertEqual(type(answer()), int)

def test_expected(self):
"answer() returns 42"
self.assertEqual(answer(), 42)

class TestSchool(unittest.TestCase):

def test_food(self):
school = School()
self.assertEqual(, 'awful')

def test_age(self):
school = School()
self.assertEqual(school.age(), 300)


1. Start all your test class names with `Test`, and always subclass

2. Start all your test method names with `test`.

3. What a test class and/or its methods _actually test_ is entirely up to you.
In some sense it is an artform. Just use the test classes to group a bunch
of methods that seem logical to go together.

4. The methods of `TestAnswer` have docstrings, while the methods on
`TestSchool` do not. For more verbose output modes, green will use the
method docstring to describe the test if it is present, and the name of the
method if it is not. Notice the difference in the output below.

### Running Green ###

To run the unittests, we would change to the parent directory of the project
(`/home/user` in this example) and then run `green proj`.

**In a real terminal, this output is syntax highlighted**

$ green proj
Ran 4 tests in 0.000s

OK (passes=4)

Okay, so that's the classic short-form output for unit tests. Green really
shines when you start getting more verbose:

**In a real terminal, this output is syntax highlighted**

$ green -v proj
. answer() returns 42
. answer() returns an integer
. test_age
. test_food

Ran 4 tests in 0.001s

OK (passes=4)


1. Green outputs clean, heirarchical output.

2. Test status is aligned on the _left_

3. Method names are replaced with docstrings when present.

4. Green always outputs a summary of statuses that will add up to the total
number of tests that were run. For some reason, many test runners forget
about statuses other than Error and Fail, and even the built-in unittest runner
forgets about passing ones.

5. Possible values for test status (these match the `unittest` short status characters exactly)
- `.` Pass
- `F` Failure
- `E` Error
- `s` Skipped
- `x` Expected Failure
- `u` Unexpected pass  
File Type Py Version Uploaded on Size
green- (md5) Source 2014-06-18 22KB